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Assessing the impact of real-time price visualization on residential electricity consumption, costs, and carbon emissions
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Resources, Energy and Infrastructure.ORCID iD: 0000-0003-4938-8862
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering.
KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering.
2015 (English)In: Resources, Conservation and Recycling, ISSN 0921-3449, E-ISSN 1879-0658, Vol. 124, p. 152-161Article in journal (Refereed) Published
Abstract [en]

The development of smart grid projects, with demand side management as an integral part, has led to an increased interest of households’ willingness to react to different types of demand response programs. This paper presents a pilot study assessing the impact of real-time price visualization on residential electricity consumption, and its effects on electricity costs and carbon (CO2eq) emissions. We analyze changes in electricity consumption based on a test group and a reference group of 12 households, respectively. To allow for analysis on load shift impact on CO2eq emissions, hourly dynamic CO2eq intensity of the Swedish electricity grid mix is calculated, using electricity generation data, trading data, and fuel-type specific emission factors. The results suggest that, on average, the test households shifted roughly 5% of their total daily electricity consumption from peak hours (of high electricity price) to off-peak hours (of low electricity price) as an effect of real-time price visualization. However, due to the mechanisms of the Swedish electricity market, with a negative relation between spot price and CO2eq intensity, the load shift led to a split effect; electricity costs modestly decreased while CO2eq emissions increased. In addition, any indication of the contribution of real-time spot price visualization to a reduction in overall household electricity consumption level could not be found, as the relative difference in consumption level between the test households and the reference households remained constant during both the baseline period and the test period. 

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 124, p. 152-161
Keywords [en]
Demand-response; Real-time electricity price visualization; Residential electricity consumption; CO2 emissions; Dynamic CO2 intensity
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-239182DOI: 10.1016/j.resconrec.2015.10.007ISI: 000403860200015Scopus ID: 2-s2.0-84951764359OAI: oai:DiVA.org:kth-239182DiVA, id: diva2:1264232
Note

QC 20181120

Available from: 2018-11-19 Created: 2018-11-19 Last updated: 2018-11-20Bibliographically approved
In thesis
1. Energy Feedback and Demand Response Strategies: Exploring Household Engagement and Response Using a Mixed Methods Approach
Open this publication in new window or tab >>Energy Feedback and Demand Response Strategies: Exploring Household Engagement and Response Using a Mixed Methods Approach
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Real-time energy feedback (EF) and demand response using dynamic pricing tariffs (DR) have been suggested as effective intervention strategies to meet the need for increased energy efficiency and demand flexibility in the residential sector. Although previous studies provide some empirical support for the effectiveness of EF and DR, evaluation approaches used in practical experiments and field trials commonly suffer from several methodological shortcomings, preventing deeper of knowledge on the potential and barriers for EF and DR to influence household energy consumption.

This thesis explored the potential of employing a mixed methods approach for evaluation of household energy consumption to provide improved understanding on how and why households engage and respond to EF and DR strategies. Three research objectives were set: 1) Analysis of the potential for using high-resolution data from smart meters in evaluation of household energy consumption and response to DR strategies, 2) development of a conceptual framework for evaluation of household responses to EF and DR strategies and analysis of its potential to increase understanding of household responsiveness, and 3) identification and analysis of household motivations, perceptions, and obstacles to engaging in EF and DR strategies.

The work to achieve these objectives followed a mixed methods research methodology grounded on literature reviews and empirical studies in real-life settings in a single case study, an EF/DR field trial taking place in Stockholm Royal Seaport. A combination of quantitative and qualitative methods was used for data collection and analysis, comprising interviews, surveys, and statistical analysis of smart meter energy data.

The results suggest that the mixed methods approach addresses several of the limitations and challenges associated with previous evaluation approaches. As regards objective (1), it was found that high-resolution data from smart energy meters can provide evaluation outcomes with increased transparency and accuracy. Regarding objective (2), it was found that the proposed framework can increase understanding of variations in household responsiveness to EF and DR strategies and reveal the relationship between impacts on electricity use and factors influencing energy consumption behavior. As regards objective (3), several obstacles for households to engaging in EF and DR strategies were identified, primarily related to household-individual factors such as knowledge, sense of control, and personal values and attitudes. Based on these findings, key issues and areas for further research are proposed.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. p. 51
Series
TRITA-ABE-DLT ; 1825
Keywords
Energy feedback; demand response; household energy consumption; energy efficiency and conservation, demand flexibility; smart grids; smart homes
National Category
Energy Systems
Research subject
Industrial Ecology
Identifiers
urn:nbn:se:kth:diva-239303 (URN)978-91-7729-984-4 (ISBN)
Public defence
2018-12-12, F3, Lindstedtsvägen 26, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20181120

Available from: 2018-11-20 Created: 2018-11-19 Last updated: 2018-11-20Bibliographically approved

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